Estimating soil texture from sample density

Abstract

A number of laboratory methods for determining soil physical fractions have been proposed. The methods being cumbersome and time consuming cannot be adopted for routine analysis in soil testing laboratories. Therefore, a simple method which could provide quantitative estimates of the soil size fractions is required. This study used soil sample density (ratio of mass of soil in a standard scoop to its volume) to estimate soil separates. Regression models were developed for predicting soil separates from sample density. Sand, silt, and silt+clay fractions were best described by second degree polynomials with coefficients of determination ranging from 0.75–0.80. Although the exponential function was statistically equivalent to the second degree polynomial for estimating clay, it was preferable as it yielded a better shape of the fitted curve at sample densities <1.2 g cm^‐3. Validation of the models with independent data showed that model‐predicted values of various size fractions matched well with laboratory measurements with coefficients of correlation ranging between 0.95–0.99. The higher correlation coefficients between the measured and estimated clay, silt, and sand fractions both for model development and their validation on independent data suggest that the models could be used for estimating soil separates from sample density measurements.